The aim of this work was to build up a simulation model of separation train design for oil and gas separation in order to investigate the effect of varying operating pressure and temperature on oil and gas flow rate. The operating conditions can have a remarkable impact on the quantity of the oil and gas production and therefore maximizing the profit. The simulation is conducted using Aspen HYSYS. The simulation result showed that increasing the 1st stage and 2nd stage pressure the production of oil is reduced and gas rises. In contrast, reducing 1st stage and 2nd stage temperature oil production rises. The study represents a powerful optimization tool for the selection of optimum operating pressure and temperature values for an offshore oil and gas separation train in order to maximize the profit of oil and gas sales. Response surface methodology (RSM) was performed by subsequent construction of Multiple linear regression (MLR) model for the chosen responses to determine the optimum operating point that generates a greatest impact on profit. Multiple regression model revealed the optimum outcome of the profit function. To conclude, RSM was successfully predicted the optimum operating conditions for maximum profit that occurs at P1 = 38.08 bar, T1 = 54.09℃, P2 = 18.00 bar and T2 = 40.56℃ predicted at 0.208 milli. $/day. Thus, the overall separation process optimized in terms of profit function under the constraints of 1st and 2nd stage temperature and pressure.